• Journal of Internet Computing and Services
• /
• v.8 no.5
• /
• pp.81-89
• /
• 2007

In this thesis, we propose ontology based context-aware recommendation system using concept hierarchy(OCARCH), Context-aware recommendation services are useful to provide an user with relevant information and/or services bared on his current context, However several approaches to context-aware recommendation system have been already proposed, each of them provide information without considering level of information concept bared on his current context, For this reason, we propose OCARCH as system capable of helping people to find their way quickly and easily through large amounts of information by determining level of information concept based on his current context, We are also using prefetching algorithm to store recommendation information that the user is likely to need in the near future based on current predictions, Therefore the OCARCH enables users to obtain relevant information efficiently, Several experiments are performed and the experimental results show that the proposed system provides more effective than conventional context-aware recommendation system.

• The KIPS Transactions:PartA
• /
• v.11A no.7 s.91
• /
• pp.529-536
• /
• 2004

Smart homes integrated with sensors, actuators, wireless networks and context-aware middleware will soon become part of our daily life. This paper describes a context-aware middleware providing an automatic home service based on a user's preference. The context-aware middle-ware utilizes 6 basic data for learning and predicting the user's preference on the multimedia content : the pulse, the body temperature, the facial expression, the room temperature, the time, and the location. The six data sets construct the context model and are used by the context manager module. The log manager module maintains history information for multimedia content chosen by the user. The user-pattern learning and pre-dicting module based on a neural network predicts the proper home service for the user. The testing results show that the pattern of an in-dividual's preferences can be effectively evaluated and predicted by adopting the proposed context model.

• Journal of Korea Multimedia Society
• /
• v.12 no.9
• /
• pp.1252-1261
• /
• 2009

One notable challenge in video searching and summarizing is extracting semantic from video contents and annotating context for video contents. Video semantic or context could be obtained by two methods to extract objects and contexts between objects from video. However, the method that use just to extracts objects do not express enough semantic for shot or scene as it does not describe relation and interaction between objects. To be more effective, after extracting some objects, context like relation and interaction between objects needs to be extracted from conversation situation. This paper is a study for how to detect speaker and how to compose context for talking to annotate conversation context. For this, based on this study, we proposed the methods that characters are recognized through face recognition technology, speaker is detected through mouth motion, conversation context is extracted using the rule that is composed of speaker existing, the number of characters and subtitles existing and, finally, scene context is changed to xml file and saved.

• The Journal of the Korea Contents Association
• /
• v.11 no.4
• /
• pp.101-111
• /
• 2011

Due to recent development in wireless communication technologies and mobile information devices, the services on ubiquitous computing technology without time and place restriction have been spotlighted. Moreover, the interest of the Wireless Sensor Networks (WSNs) and context-awareness technologies have largely been escalating and their technologies utilization is active in the various applications such as healthcare, farm management and so on. However, the direct adaption of the existing context-awareness technique to the WSN technology has several drawbacks as follows. First, such systems waste precious energy of sensor nodes, due to unnecessary data transmissions. Secondly, since the existing work was designed to support only specific applications, it is required to implement a new context-awareness application for a specific purpose. Therefore, we, in this paper, propose a new real-time monitoring system based on context-awareness in WSNs. Our system not only enhances energy efficiency by reducing data transmissions by doing context-awareness on a sensor node, but also is scalable in terms of supporting new context-awareness functionalities through modularization.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.5
• /
• pp.587-592
• /
• 2004

Context-aware computing systems require real-time context reasoning process for context awareness. Context reasoning can be done by comparing input information from sensors with knowledge-base within system. This method is identical with it of rule-based systems. In this paper, we propose hardware rule-based system architecture which can process context reasoning in real-time. Compared to previous architecture, hardware rule-based system architecture can reduce the number of constraints on rule representations and combinations of condition terms in rules. The modified content addressable memory, crossbar switch network and pre-processing module are used for reducing constraints. Using SystemC for description can provide easy modification of system configuration later.

• Convergence Security Journal
• /
• v.14 no.7
• /
• pp.75-84
• /
• 2014

The advancement in ubiquitous healthcare specifically in preventive healthcare can lead to longer life expectancy especially for the elderly patients. To aid in preventing premature loss of lives as well as lengthening life span, this research aims to implement the use of mobile and wireless sensor technology to improve the quality of life and lengthen life expectancy. The threats to privacy and security have received increasing attention as ubiquitous healthcare applications over the Internet become more prevalent, mobile and universal. Therefore, we propose Context-aware Service of U-Healthcare Application based Knowledge using Ontology in secure health information exchange. This research also applies ontology in secure information exchange to support knowledge base, context modeling, and context reasoning by applying the general application areas for ontologies to the domain of context in ubiquitous computing environments. This paper also demonstrates how knowledge base, context technologies, and mobile web services can help enhance the quality of services in preventive ubiquitous healthcare to elderly patients.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.2
• /
• pp.514-522
• /
• 2017

Traffic offloading is a promising solution to solve the explosive growth of mobile traffic. One of offloading schemes, in LIPA/SIPTO(Local IP Access and Selected IP Traffic Offload) offloading, we can offload mobile traffic that can satisfy QoS requirement for application. In addition, it is necessary for traffic offloading using social context due to large traffic from SNS. Thus, we propose the LIPA/SIPTO offloading algorithm using social context. We define the application selection probability using social context, the application popularity. Then, we find the optimal offloading weighting factor to maximize the QoS(Quality of Service) of small cell users in term of effective data rate. Finally, we determine the offloading ratio by this application selection probability and optimal offloading weighting factor. By performance analysis, the effective data rate achievement ratio of the proposed algorithm is similar with the conventional one although the total offloading ratio of the proposed algorithm is about 46 percent of the conventional one.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.3
• /
• pp.291-296
• /
• 2006

In context-aware computing environment, some context is characterized by a single event, but many other contexts are determined by a sequence of events which happen with some timing constraints. Therefore context inference could be conducted by monitoring the sequence of event occurrence along with checking their conformance with timing constraints. Some context could be described with fuzzy concepts instead of concrete concepts. Multiple entities may interact with a service system in the context-aware environments, and thus the context inference mechanism should be equipped to handle multiple entities in the same situation. This paper proposes a context inference model which is based on the so-called fuzzy colored timed Petri net. The model represents and handles the sequential occurrence of some events along with involving timing constraints, deals with the multiple entities using the colored Petri net model, and employs the concept of fuzzy tokens to manage the fuzzy concepts.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.1
• /
• pp.21-26
• /
• 2008

It was already realized at a current technological level of home network systems that the systems recognizes a user's simple order and carry out the order in the ubiquitous computing environment. However home is not a simple environment consisting into a large number of family members, so various order and situation would be needed accordingly. From now on we need to reach the technological level to infer that how is the user's behavior patterns and what kinds of service is the fittest to user who belong to the ubiquitous computing environment by using the result of the context interpreter. In this regards, active inferred-model needs to be suggested upgrading user's command into one step more higher level than the simple one adapting diversified feature. This study would like to suggest this active model recognizing context, which is user's environmental information applying basic network and inferring Context-based Service that user wants through the recognized result This study proposes a new method that can infer the user's desire in ubiquitous computing environment. First of all, we define a context as user's information of ubiquitous computing environment situation that user belongs to and we classify the context into 4W1H(Where, Who, When, What) formats. We construct Bayesian network and put the factor of context use as Bayesian network nodes. As a result, we can infer the user's behavior pattern and most proper service for user in the intelligent space from the probabilistic result of Bayesian network.

• Korean Journal of Cognitive Science
• /
• v.13 no.4
• /
• pp.9-21
• /
• 2002

Four experiments were conducted to examine whether maintaining the same conceptual context across study and test would affect performance on a perceptual implicit memory task. The sense-specific theory of priming (Lewandowsky et al., 1989) predicts greater priming from a match in conceptual context across study and test compared with a condition in which the conceptual context is mismatched, whereas the transfer-appropriate-processing view (e.g., Blaxton, 1989) predicts no difference. In experiment 1 and 2, little or no effect of varying context was observed on a implicit task. In experiment 3 and 4, a process-dissociation procedure (proposed by Jacoby, 1991) was used to separate automatic influences from consciously controlled influence in implicit memory, which was measured by Korean word completion task. The results showed that conceptual context effect was observed in consciously controlled parts of implicit memory. These results suggest that only consciously controlled processing parts of implicit memory is sensitive to conceptual context.